2019
Applying a deep learning-based sequence labeling approach to detect attributes of medical concepts in clinical text
Xu J, Li Z, Wei Q, Wu Y, Xiang Y, Lee H, Zhang Y, Wu S, Xu H. Applying a deep learning-based sequence labeling approach to detect attributes of medical concepts in clinical text. BMC Medical Informatics And Decision Making 2019, 19: 236. PMID: 31801529, PMCID: PMC6894107, DOI: 10.1186/s12911-019-0937-2.Peer-Reviewed Original ResearchConceptsSequence labeling approachMedical conceptsEntity recognitionRelation classificationClinical textDetection taskBidirectional long short-term memory networkLong short-term memory networkShort-term memory networkConditional Random FieldsSequence labeling problemTraditional methodsNLP applicationsBi-LSTMNeural architectureLabeling problemLabeling approachMemory networkNovel solutionRandom fieldsHigh accuracyEfficient wayTaskAttributesClassification
2015
A comparison of conditional random fields and structured support vector machines for chemical entity recognition in biomedical literature
Tang B, Feng Y, Wang X, Wu Y, Zhang Y, Jiang M, Wang J, Xu H. A comparison of conditional random fields and structured support vector machines for chemical entity recognition in biomedical literature. Journal Of Cheminformatics 2015, 7: s8. PMID: 25810779, PMCID: PMC4331698, DOI: 10.1186/1758-2946-7-s1-s8.Peer-Reviewed Original ResearchMachine learning-based systemsConditional Random FieldsLearning-based systemEntity recognition systemSupport vector machineEntity recognitionRecognition systemF-measureChallenge organizersDrug Named Entity RecognitionVector machineStructured support vector machineMicro F-measureInformation extraction tasksWord representation featuresNamed Entity RecognitionTest setRandom fieldsPrimary evaluation measureBrown clusteringDocument indexingIndividual subtasksExtraction taskRandom IndexingBiomedical domain
2010
Recognizing Medication related Entities in Hospital Discharge Summaries using Support Vector Machine.
Doan S, Xu H. Recognizing Medication related Entities in Hospital Discharge Summaries using Support Vector Machine. Proceedings - International Conference On Computational Linguistics 2010, 2010: 259-266. PMID: 26848286, PMCID: PMC4736747.Peer-Reviewed Original ResearchSupport vector machineHospital discharge summariesConditional Random FieldsDischarge summariesMedication namesRelated entitiesClinical textVector machineType of medicationNamed Entity Recognition (NER) taskEntity recognition taskRule-based systemBest F-scoreI2b2 NLP challengeTypes of featuresF-scoreI2b2 challengeNLP challengeNER systemSemantic featuresRecognition taskMachineData setsRandom fieldsBetter performance